At Inscribe, Ivo’s first user conference, we announced three developments in our mission to push contract intelligence forward: Ivo Collaborate, a new way to leverage and apply contract intelligence across intake, negotiation, and approval; the Ivo–Micro1 Contract Bench, a benchmark for measuring AI’s actual judgment and effectiveness in contract review; and Ivo Sage, an open-source AI model post-trained for long-horizon contract work.
Together, these announcements reflect a broader shift away from software that simply organizes contracts workflows towards technology that reflects the way lawyers actually work while enabling them to uplevel their value to the business. With these releases, Ivo aims to not only reveal the business intelligence hidden within contracts, but to provide the frameworks and technology that will advance it even further.
Ivo Collaborate brings the entire contracting process into one place, from intake through negotiation, approval, and signature. Collaborate gives the negotiation process itself a system to live in: it allows the decisions, positions, and concessions that shape each deal to be managed in context and in one location, all while retaining the data from that process as intelligence that your team can utilize going forward.
Unlike how a CLM simply routes documents based on a predefined field, Collaborate actually reads each contract as it arrives, then assesses the agreement against the playbooks and rules set by the legal team before routing it accordingly. Low-risk agreements can move directly to signature, while those with risks that require further judgment are escalated to the right reviewer, with all the relevant context already identified.
With Collaborate, anyone in the organization can start a deal request directly, removing the traditional legal bottleneck at intake while making sure that legal’s judgment is consistently and effectively applied across all the organization’s agreements. The result is a system where legal can define how the business contracts across every deal without the need for laborious manual review, and all while capturing what the organization learns along the way—turning every negotiation into an opportunity to make the next deal smarter.
Read more about Collaborate on our blog here.
Ivo has released a new contract review benchmark, developed in collaboration with data lab and research partner Micro1. The Ivo–Micro1 Contract Bench was developed to evaluate aspects of contract review that conventional AI benchmarks can miss. Many existing approaches to evaluating AI models for contract work focus on whether the model can simply identify issues and make edits. However, real contract review requires knowing things like what not to change, how to adapt a position to the deal’s circumstances, how to execute established positions in context, and how to effectively recognize when an issue should be escalated to a human. Most models aren’t judged on these kinds of nuances, like the precision, efficiency, and effectiveness of edits.
The Ivo–Micro1 Contract Bench evaluates contract review effectiveness based on the decisions and judgement calls that real attorneys make. Our contract bench evaluates models across five dimensions: issue prioritization, negotiation restraint, situational judgment, escalation judgment, and standard-position execution. Ivo–Micro1 Contract Bench thus uses contract-review tasks, detailed playbooks, deal context, and counterparty redlines in its review, with the criteria used to evaluate model decisions established by real attorneys.
Early findings show that, against these benchmarks, leading models concede easily and push back poorly: when the right response is to counter or reject a provision, they get it right only 46% of the time. When the right response is to escalate an issue to management, the leading models meet only 23% of the escalation criteria. These results highlight a real discrepancy between existing review standards and criteria that would lead to meaningful and effective review.
A public set of these benchmark results, along with the dataset used for the benchmark criteria, will be available in the coming weeks.
Ivo research efforts have also produced Ivo Sage, an open-source model that is the first to be post-trained for long-horizon contract work. General-purpose frontier models are built to handle a wide range of tasks; however, contracting requires a much more specialized set of skills. Contracts are long and complicated documents, necessitating multi-step legal reasoning and deep context to adequately review. Post-training gives an AI model the opportunity to learn these patterns and tasks more effectively and surgically, rather than approaching every contract as a general-purpose problem.
The Ivo Sage model was built in partnership with River AI by post-training DeepSeek V4 Flash specifically for complex contract work. This was done using both public and synthetic data generated by real attorneys, with River providing valuable technical and training infrastructure support. After reinforcement learning, the model went from scoring 70% of the pass criteria of the Legal Agent Benchmark (LAB) Contracts to 91%. Overall, Ivo Sage reached comparable quality of much larger frontier models, with higher token efficiency at a fraction of the cost.
Unlike other legal AI companies, Ivo is releasing the Ivo Sage mode as an open-source model. Ivo Sage is being released along with its research and evaluation record so that researchers, developers, and legal tech builders can download it, study how it performs, and build on it. Our goal is to make progress in legal AI more transparent and collaborative. By sharing our model and the work behind it, Ivo is hoping to give others a foundation they can test and improve as contract-specific AI continues to develop.
Ivo Sage is available to download on Hugging Face here.
Ivo is committed to making everything surrounding contracts better, smarter, and more intelligent. That means building technology that can meet the complexity of legal work, creating new ways to improve what AI can do, and making the underlying research accessible enough to move the whole field forward.
Our work is still evolving, but the direction is clear: a future where contracts are not just documents to manage, but intelligence that moves the business.
Ten sessions, two tracks, one day. Here's how to decide where to be.
Inscribe starts at 9:30 with HubSpot's chief legal officer and Ivo CEO Min-Kyu Jung discussing how AI will transform the future of legal and contracting. The day closes at 4:15 with another fireside chat with Ivo VP of Partnerships Kristin Hagan and Acrew Capital's Aliisa Rosenthal, who joined OpenAI as its first commercial hire and spent three years watching a thousand enterprises attempt the same change most companies are attempting now.
The Strategic Track tackles the big-picture issues facing legal teams today: how to roll out new systems of working, how to position legal as a partner in the business, and how to parlay legal knowledge into nontraditional roles as the field evolves.
The Practitioner Track is about how the work actually gets done: practical tips on building systems, crafting playbooks, and solving the specific contracting problems your team experiences every day.
Every time slot has a session from one of each running concurrently, so feel free to go between the two tracks and build your perfect agenda out of the sessions that speak to you.
10:30 a.m. - Driving Adoption Across a Team. Join this session to hear real solutions to the problems millions of teams are living in 2026: the AI pilot went well, a few people became power users, and then nothing moved for months. Contract ops leaders from IBM and Intel will speak on how to find the internal champions, set expectations that survive the novelty wearing off, and bring skeptics along without slowing down the people already moving.
11:25 a.m. - Building Playbooks Your Team Will Actually Follow. This session is the logical follow-up to Driving Adoption Across a Team. Adoption often fails when standards aren’t consistently upheld, and an effective playbook is key to a successful rollout. This session discusses how to craft playbooks that hold up under deal pressure, stay current as the business shifts, and are applied the same way across reviewers.
2:40 p.m. - Legal Ops as a Strategic Function. This session features legal ops leaders from DoorDash, Figma, and LegalOps.com discussing what they’re automating and how the role is changing. They’ll discuss the variety of functions owned by legal ops teams and how each panelist has formed their own approach.
That leaves 1:45 open. Take Under the Hood if you're still evaluating tooling.
10:30 a.m. - From Back Office to Business Partner. Hear from senior counsel from Pinterest, Atlassian, and Vercel, who have all moved legal teams from decision reviewers to business strategists. You'll hear how legal knowledge holds business insights, how these panelists earned earlier involvement in decisionmaking, and what changed once they became partners with the rest of the business.
11:25 a.m. - Contract Intelligence as a Source of Business Insight. This session is all about the argument for legal becoming the function that holds answers for the rest of the org. A contract portfolio is the full record of every promise made and every dollar owed, and is a major asset in the business that almost nobody leverages. This session will discuss the insight held in contracts and how to hand off that information to procurement, finance, and sales ops.
2:40 p.m. - Legal Ops as a Strategic Function pairs well with both to round out the day.
1:45 p.m. - Under the Hood. Our Head of Engineering will talk about the legal AI problems users never see: scaling to millions of contracts, keeping everything secure and fast, and turning a prototype into infrastructure a global legal team can rely on. He’ll cover the constraints that shaped Ivo and the bets that paid off. If you're in a buying process, this is the closest thing on the agenda to technical due diligence.
2:40 p.m. - Ivo Live. No slides, no script. Our legal engineering team takes whatever problems you bring and works through it in front of the room, thinking out loud as they go. You'll see how the work actually gets done, and even how others in the audience might approach the same thing.
1:45 p.m. - Non-Traditional Career Paths in Legal. Lawyers who left practice for legal engineering, product marketing, and revenue leadership discuss how they leveraged their JD and legal experience into their current positions. Hear from the president of an alternative legal services provider, a principal product marketing manager at Adobe, and many more. Part career conversation, part peek at where legal talent is heading, this session is useful if you're weighing a move yourself (or trying to keep someone else who is).
All Day - Ivo Genius Bar. If you can’t make Ivo Live or prefer one-on-one assistance with your contracting questions, be sure to visit our Genius Bar. Bring a question you've been meaning to put to an Ivo expert - no appointment necessary - and one of our expert staff will walk you through it on the spot.
All Day - Features Request Board. Lawyers who left practice for legal engineering, product marketing, and revenue leadership, including the president of an alternative legal services provider and a principal product marketing manager at Adobe. Part career conversation, part look at where legal talent is heading. Useful if you're weighing a move yourself, and equally useful if you're trying to keep someone who is.
Thursday, October 1st, 2026
Terra Gallery, 511 Harrison Street, San Francisco
Registration 8:00 a.m., sessions end 5:00 p.m., reception until 7:00 p.m.
Ivo's first user conference Inscribe will take place on October 1st, 2026 in San Francisco. One day, ten sessions across two tracks, plus an opening keynote and two fireside conversations.
The Strategic Track explores the bigger questions facing legal teams today. The Practice Track looks at how to put those ideas to work. Attendees can mix and match sessions from either one.
Here's the full day.
9:00–9:30 a.m.
Our CEO and co-founder will open the conference with a special keynote address. Companies measure almost everything they do, and then leave the contract portfolio — the record of every promise made and every dollar owed — largely unread. This is the case for changing that, and for what it means when contracts start informing how a business actually runs.
9:30–10:00 a.m. — AI transformation and the future of legal and contracting
Our CEO stays on stage with the chief legal officer of one of the world's largest software companies, whose team is responsible for making sure the AI their company ships is fast, secure, and something customers can trust. That's the problem most of this room is working on now, from one side or another. The conversation is about where contracting goes as AI takes on more of the work, and what legal owns as it does.
10:30–11:15 a.m. — In-house counsel on how to go from reviewing decisions to making them
For a long time, legal was where decisions went to get checked, not made. That's changing. The strongest teams are moving upstream, shaping strategy early instead of reacting to it late. This panel brings together senior legal leaders who've made that shift, speaking candidly about how legal stops being a gate and starts becoming a strategic partner.
11:25 a.m.–12:10 p.m. — Legal leaders on how to use contract data to inform business strategy
Companies measure their sales down to the lead, track finance to the cent, and instrument operations end to end — and then leave the contract portfolio, the full record of every promise made and every dollar owed, largely unread. This session makes the case for contract intelligence as a genuine source of business insight, and for legal's role in surfacing answers that procurement, finance, and sales ops keep coming to ask for.
1:45–2:30 p.m. — Former lawyers on the transition out of practice and the future of legal work
A law degree opens more doors than most people expect. This session brings together people who trained and practiced as lawyers and have since moved into other functions, from legal engineering to marketing and beyond, to talk about the paths they took, the skills that carried over, and how they think about a legal career in a moment when the work itself is changing. Part career conversation, part look at where legal talent is headed next.
2:40–3:25 p.m. — Legal ops leaders on how they uplevel their work with AI in a changing industry
Legal ops has grown from a nice-to-have into the engine that keeps a modern legal team running, and no two functions look alike. This panel brings together legal ops leaders across different stages and segments to compare notes on what they own, what they automate, where they can add the most value, and how the role is changing as AI reshapes the work.
10:30–11:15 a.m. — Contract ops leaders on going from successful AI pilot to org-wide use
Many companies have the exact same experience: pilot goes well and a few people become power users, then use stalls for months. The issue is rarely the technology itself; it's the work of shifting how a team operates day to day. This session is a candid conversation about moving a group from curiosity to a completely new way of working: finding the internal champions who carry adoption further than any mandate, setting expectations that hold once the novelty fades, and bringing skeptics along without slowing the people already moving.
12:00–12:35 p.m. — Legal experts on crafting playbooks that become practice
Every legal team has a playbook, and most of them exist in a document nobody opens after onboarding. The gap between the standard that was written and the one your team applies at 6 p.m. on a Friday is where potential risk compounds. This session gets into the craft of building playbooks that hold up under real deal pressure: clear enough to follow, current even as the business shifts, and applied consistently across reviewers and review cycles.
1:45–2:30p.m. — Building an AI platform that serves the global enterprise with Ivo's Head of Engineering
Our Head of Engineering on what it takes to build a legal AI platform that's both reliable and rigorous enough for the world's largest companies. A few years ago, Ivo was a small startup. Today, it runs contract work for some of the biggest enterprises in the world. That process required solving hard problems most users never see: scaling to millions of contracts, keeping everything secure and fast, and turning a promising prototype into infrastructure a global legal team can rely on. He walks through what the process required, what bets paid off, and how Ivo became what it is today.
2:40–3:25 p.m. — Bring the problem you're stuck on and watch our legal engineering team work it out in real time
A hands-on breakout with no slides and no script. Bring the problems you're actually stuck on, and our legal engineering team will work through them live with Ivo, breaking down the process as they go. Part workshop, part problem-solving session, this session is a chance to see how others in the room would approach the same challenge.
4:15–5:00 p.m. — Lessons learned from company hypergrowth and a thousand enterprise AI rollouts
Our VP of Partnerships closes the day with someone who joined a frontier AI lab as its first commercial hire, back when the sales team was two people and the product everyone now uses didn't exist. She spent the next three years building the commercial organization behind it, and watching a thousand enterprises attempt their own version of the same change. She's now a General Partner at a venture firm investing in what she calls the second wave of AI. If you want to know what moves enterprise AI adoption and what stalls it, this is the conversation.
A Genius Bar with Ivo experts on hand to answer any and all questions about the product, a Feature Request Board where people can share ideas for new features and upvote their favorites, and a reception from 5 to 7 p.m. once the sessions are done.
Thursday, October 1st, 2026 Terra Gallery, 511 Harrison Street, San Francisco Registration opens at 8:00 a.m., sessions end at 5:00 p.m., reception until 7:00 p.m.
Contracts touch every part of the business, but the process around them is scattered. A request comes in over email. A draft lives on someone's desktop. Approvals happen in Slack. Finance flags a term three weeks late, and which "final" version is the right one is anyone's guess.
The work that actually decides a deal—the negotiation—has never had a system built to run it. So every new deal starts over from scratch. You chase down whoever worked on the last one like it, dig through old threads to see where things stand, or take a guess with your best judgment and push forward. Meanwhile the deal slows, and the intelligence that could have been created along the way—every position taken and concession made—disappears the moment the ink dries.
We at Ivo wondered: what if the whole process ran in one place, and every negotiation made the next one smarter?
Collaborate orchestrates the entire contracting lifecycle, from intake through approval, negotiation, and signature. It reads every agreement as it arrives, routes it based on the risk you define, and keeps every version, approval, and decision in one place.
And because the negotiation is finally running in one system, Collaborate learns from it. The back-and-forth where deals are won or delayed becomes intelligence your team retains and uses for the next one.
Collaborate is the layer between the deal and the signature. Where a traditional CLM routes documents based on inflexible rules and blind to what's inside them, Collaborate reads each agreement and runs the process around it.
Most contract work starts with a bottleneck right out of the gate: someone in the business needs an agreement, so they email legal and wait.
With Collaborate, intake is self-serve. Business users can start a deal request themselves, from the systems they already use, either by creating an agreement from a template or uploading one from the counterparty. Collaborate reads each document as it arrives, detects the type, extracts the relevant information, assesses its risk against your playbooks, links it to the opportunity in your CRM, and routes it to the right person.
There are no forms to fill and no fields to tag. Your team then confirms what Collaborate found, instead of keying it in by hand.
Once an agreement arrives, Collaborate reads it and produces a single issues list. All routing and approvals can now happen in one space, directly in Collaborate. Counsel can settle, redline, or escalate each issue directly from the issues list, either in the browser or in Word, and the list updates for everyone the moment it changes. Agreements that you define as low-risk can be automatically approved and sent straight to signature. Ivo can be set up so that low-risk agreements, as defined by your organization, are automatically approved and sent straight to signature. Anything that needs further review stays open, with the deal context already attached, until the designated person weighs in. You decide which issues “pass” and which “fail” and get escalated, so the issues list always reflects your own playbooks—not just a generic workflow.
Once a deal is in motion, Collaborate lets the whole process live in one single place.
Legal, sales, finance, and the counterparty can all work from the same deal, with every version and approval tracked beside it. The full history is right there: who changed what, who approved it, and where it stands today. The answer to "where are we on this" is on the screen, not forensically reconstructed from a weeks-old email thread.
Because the negotiation runs in one place, it becomes something you can learn from. Collaborate can answer questions legal could never answer before, like:
Over time, Collaborate can make proactive recommendations on how to update your playbooks, based on how your organization has negotiated before. Every deal you close teaches the next one.
We built Collaborate because our most sophisticated customers already work this way: their lawyers proactively write the rules that govern risk across the whole portfolio, rather than reviewing each agreement on its own and in a vacuum. That is the shift that Collaborate is built for: putting legal's invaluable insight and expertise at the center of every deal the business makes.
With Collaborate, Ivo now covers the full contracting lifecycle, from intake and negotiation through approval and signature, alongside Ivo Intelligence, Ivo Review, and Ivo Assistant.
Ivo Collaborate is available today. Request a demo and join the growing number of enterprise legal teams running their deals on Collaborate. If you'd like help getting your team set up, our solutions attorneys are here to help.
Earlier this month, Caitlan Rocha, Ivo’s In-House Counsel, led a roundtable of general counsel at The L Suite’s 2026 Legal AI Conference. A few years ago, the conversation around AI in legal centered on one question: Will it replace lawyers? Today, that debate has largely disappeared.
Instead, legal leaders from industries like financial services, healthcare, tech, and media spent the session discussing something much more immediate: how to leverage AI to keep pace with an ever-growing volume of legal work while protecting their organizations.
The conversation Caitlan led centered on how fast the work is piling up, and how thin legal teams are stretched trying to keep pace. Several leaders described feeling buried under the sheer volume of work.
It's not hard to understand why. Like we often say at Ivo, everything starts with an agreement. You can't hire an employee, purchase software, engage a vendor, or sell a product without a contract. And as companies grow, so does the number of counterparties they manage.
Ironically, many of the technologies companies adopt to become more efficient generate even more contracts to review. Every new software category brings new vendors. Every vendor relationship comes with its own MSA, NDA, security review, data processing agreement, and procurement process.
Legal teams are left trying to solve an impossible equation: workloads continue to grow while resources largely don't. At the same time, every function around them increasingly assumes AI has already solved the problem.
At this point, most legal leaders have moved beyond asking whether AI can help. They know it can. Many organizations have even mandated AI adoption to improve productivity across the business.
But for legal and compliance leaders, the challenge isn't whether to use AI; it's how to do so responsibly.
“A number of them told me they felt like they were building the plane while flying it,” Caitlan says.
“We all follow the few relatively clear boundaries that have emerged: don't cite a case that doesn't exist, don't upload privileged documents to a public chatbot.” Beyond that, there are few established standards, and no clear timeline for when a comprehensive governance framework will emerge.
While AI regulation continues to evolve, there is still no comprehensive governance framework that answers many of the practical questions legal teams face every day, including how contract data should move through AI systems, what governance looks like in practice, or what "good" AI adoption actually looks like.
For companies in regulated industries, that uncertainty shapes every evaluation. Legal teams aren't just deciding whether a tool is valuable. They're documenting why its use is appropriate, how risks are mitigated, and how those decisions can be defended as regulatory expectations continue to evolve.
Because there are so few governance frameworks in place, companies have established their own AI governance policies, but many were written out of an abundance of caution and are too rigid to reflect the actual work employees need to do—a direct clash with employer AI mandates.
As a result, employees, including lawyers, are working around those policies already simply to keep up with the workloads they're expected to manage. Many companies are now rewriting their AI policies because the first draft didn’t reflect how people needed to work.
If there was one reassuring takeaway from the discussion, it was that no one is navigating these challenges alone. Every company is grappling with the same AI growing pains: balancing innovation with security, and productivity with governance.
Staying at the forefront of technology while trying to stay compliant and secure is incredibly difficult.
“Nobody in the room claimed to have the answer,” Caitlan says. “What they had in common was the recognition that they're adopting AI to deal with the increased workload, but they’re doing so without the familiar guardrails, decades of precedent, or fully developed governance frameworks to demonstrate they’re doing it correctly.”
That may be the biggest shift of all.
The conversation is no longer about whether AI will replace lawyers. It's about how lawyers can thoughtfully adopt AI to better support their businesses while building governance that will stand the test of time.
There isn't a tidy ending yet. The technology is evolving faster than the rules, and every legal department is learning in real time. But if the roundtable made one thing clear, it's that legal leaders aren't trying to solve these questions in isolation. They're sharing experiences, comparing approaches, and learning from one another because, for now, that's how the profession moves forward.
There’s a high chance that the contracts your team signed last quarter are already invisible to your business. While they may be stored in the cloud, in a shared folder, or in a CLM, you still can’t easily extract information from them. This is because "stored" and "findable" are two different things, and “findable" and "understandable" are even further apart.
To solve this, contracting teams have invested heavily in filing, storing, and tagging systems. However, none of these so-called solutions fix the fact that it is still extremely difficult to see what the business has already agreed to; in other words, what the contracts in these expensive storage systems actually say.
That lack of information extraction has real costs; companies need to know what their obligations are, and they rely on their legal and contracting teams to be able to quickly get them answers. If those teams can’t answer in a timely way, there’s the risk that the rest of the organization moves on, making decisions independently, without that precise contractual data. Decision-making without all the relevant information exposes the company to significant risk, which, of course, the legal department will be obligated to deal with later.
In-house legal teams are increasingly expected, and want, to be a strategically important arm of the business. They can offer informed views on crucial business matters like risk exposure, contractual leverage, and how the company's position compares to market norms. But doing so requires the ability to answer specific questions about the business's contractual positions quickly and at scale, questions such as:
These questions come up on occasions like board meetings and M&A due diligence, where legal guidance is sorely needed. Unfortunately, when legal departments can't answer these questions quickly, the business thinks they’re being slow or commercially disconnected. However, the real issue is simply that they don’t have the right tools for the job.
"Our problem is that folks can't find their contracts. They do a search and even if they filter it down, it gives them essentially everything under the sun and they're not entirely sure what's the most up-to-date contract."
Lawyers know the time cost of answering these questions when information in contracts can’t be easily found. Ivo's recent research study revealed that 80% of legal teams spend at least an hour every week manually searching inside agreements for this type of business-critical information, and 14% spend 10 hours or more: that’s a senior lawyer's entire working day, every week, spent on information retrieval rather than analysis or judgment. Every hour spent searching for contract information is an hour of a lawyer's time not spent analyzing risk, advising on a commercial decision, or helping the business think ahead. Legal teams are kept reactive by software that should be helping them to be proactive.
The root of the problem is that not very many people, and certainly not many software providers, understand just how critical contracts are to a business. Every significant commercial relationship, whether it's customers, employees, suppliers, partners, or lenders, is governed by a contract. Those contracts define what a company can and can't do, what needs to be paid and when, and what happens when things go wrong. They're the operating system that your business runs on, and if your business can’t effectively read or understand that operating system, that creates a gap between what a company has committed to and its ability to surface and act on it. That’s the real risk your business faces: one we’ve identified as a contract visibility crisis.
"Probably every big company is the same. The whole contract situation is a mess. Our CLM is a mess. We're looking at a dumpster of documents, some are linked, some are not linked, some are complete, some are not complete."
The industry has spent decades only treating the symptom of this crisis, with paper contracts being moved to filing cabinets, then to the cloud, and then to CLMs that added metadata and workflows. However, each generation made storage incrementally better without addressing the actual issue: nobody can read the contracts at scale, quickly, without manually extracting the information clause by clause.
Reading a contract the way a lawyer does (understanding concepts, following cross-references, and spotting what's unusual) used to require pure human review. However, large language models have changed that; especially since the language in contracts is precise, structured, and pattern-based, making it well-suited to be analyzed by AI.
Initially, early LLMs could produce contract-like text but couldn't reliably comprehend an existing document. The next generation of tools could answer simple questions but were prone to hallucination and lost coherence across long documents. GPT-4-class models made reviewing a single document viable, but connecting a particular clause to its implications elsewhere in the agreement still required a specific prompt telling the system where to look.
But in the last year, models have acquired the ability to conduct multi-step reasoning across long, interconnected documents. AI can now identify relationships between clauses, flag deviations from market norms without being told where to look, and treat a master agreement, its amendments, and every governed statement of work as one coherent picture.
This progression turns what once was a multi-day review of a supplier's termination rights, pricing protections, and liability caps into a query answered in minutes, with citable sources included. It lets a marketing team find which customers granted them logo rights, without getting their legal or contracting teams involved until the legal judgement stage, and lets a finance team ask which agreements carry uncapped liability and receive a downloadable table, instead of having to ask legal to make a quick, educated guess.
Seeing this progression of AI in practise, Ivo Intelligence, our contract intelligence product, illustrates what a contract intelligence platform is capable of when it accesses a portfolio of agreements:
Solving the contract visibility crisis requires the business to read its own operating system the moment it is needed, at scale, and without waiting on a manual review. The good news is that the intelligent functionality to do this now exists, meaning legal and contracting teams finally have the tools to match how much they're already expected to know about the business they support..
Most lawyers enter law school with a fairly clear picture of the career paths ahead. For most, their career path can go in one of two directions: they can either join a law firm, where they’ll grind as an Associate until they make Partner one day, or become an In-House Attorney. Both have their pluses and minuses, and are equally well-established pathways. Today, there is a third option: the role of Legal Engineer. The rise of AI-powered legal tech has brought with it a role that previously didn’t exist, and there’s a lot of discussion about what it is and what it means for the legal profession.
Alexis Nicholas, one of Ivo’s Legal Engineers and In-House Attorneys, believes she has seen the future.
“One of the best parts about Legal Engineering at an early-stage company is that it’s such a flexible and changeable role,” she says. Alexis describes her role as having four focus areas:
“The role will, of course, be different at different organizations, and the areas of responsibility will change based on what the business needs,” Alexis notes. “That’s what makes it so interesting and varied.”
Alexis points out that with these four different focus areas, she’s still very busy, but it’s a different, more directly rewarding form of busy than she experienced in traditional legal practice. “It’s the nature of startups,” she says. “Companies at this stage have a ‘do what it takes’ energy, which gives Legal Engineers much more scope to be creative and wear a lot of hats. Of course, there’s an infinite number of things to do, with the potential to keep doing more if you want to. But it’s a choice to be here and build, and I feel the excitement of being able to still be a lawyer and use my legal skills, but in a much more creative and novel way. It’s hugely fulfilling.”
To Alexis, one of the most important aspects of being a Legal Engineer is the energetic and resourceful culture at a startup and the immediate results she can deliver within it. “At a firm, being busy usually meant deep, narrow focus: all your hours spent becoming an expert within one practice area. But at Ivo, being busy means switching between different types of work in the same day: negotiating a contract, working on a product pitch, testing a new feature, joining a customer call, running a demo, prepping a webinar, initiating a new internal workflow; and that variety changes how the hours feel. It's less like grinding through billable hours on similar tasks, and more like constantly learning and being introduced to new directions. It’s more energizing because I can see the direct impact of what I'm doing, rather than working on a specific, siloed matter that your team has been helicoptered-in for.”
Legal Engineering is emblematic of a shift that’s happening in the legal profession: a slow but undeniable change in how the value of a lawyer’s work gets defined. Before AI, and in many legal roles, lawyers are, as Alexis puts it, “just a lawyer,” e.g., working on specific matters that lead to an outcome, whether that’s closing a deal, signing a transaction, or winning a case. The work lawyers do to achieve these outcomes is, albeit hugely important, a small part of a larger whole, generally in one area of specialization, and their relationship to the result for their client is remote at best. In-house attorneys get closer to that outcome, sitting inside the business and seeing decisions play out for their company in real time. But the work itself is still bound by traditional law: contracts, risk, compliance.
But as a Legal Engineer, Alexis gets that same privity to the business, but with a much wider remit, having exposure to types of work she wouldn’t typically get in a traditional legal role — public speaking, sales calls, demos, recruiting, marketing campaigns, product development meetings, and working with software engineers—and certainly not this early into a new position. The value Alexis brings is her judgment and legal knowledge, put to work across product, sales, and customer relationships, not just contracts. “It's a huge amount of learning, responsibility, and work that I'd never get to do as just a traditional lawyer,” Alexis notes. “I don’t see it as leaving the law at all, as not only do I still do legal work, but I’m also still embedded within the practice of law, just in a different way.”
All in all, a Legal Engineer’s role is a combination of legal and technical expertise, with a healthy dash of startup dynamism. And it isn’t going away. “We’re at a very interesting time in the world with AI,” Alexis says. “It feels like this century’s dot-com boom, and being a Legal Engineer is a huge opportunity to be at the heart of it. Legal AI is one of the fastest-growing corners of legal tech, so this hybrid legal-plus-product-plus-technical skill set will continue to be in demand.”
Do you have a legal background? Are you interested in trying out this third legal career path in tech? Check out our open roles!
Every in-house legal team negotiates the same clauses over and over again. With every signed deal, your team builds up valuable knowledge: what liability caps you've accepted; which indemnification language is standard for your industry; or how often mutual NDAs get pushed to one-sided. That history is a real competitive advantage, but almost none of it is accessible.
It lives in people's heads, buried in shared drives, or locked inside a CLM that nobody has time to search. So when a new agreement lands, you start from scratch. You track down whoever worked on a similar deal. You dig through old contracts. Or you make your best judgment call and move on.
That is, until today. What if you could access the full knowledge of your previously negotiated contracts with a single click?
Ivo Benchmarks gives your team institutional memory, inside your review workflow, at the precise moment you need it.
When you upload a contract into Ivo, Benchmarks automatically scores each clause against your history of executed agreements. Within seconds, you can see how a provision compares to similar contracts you've negotiated before, filtered by counterparty type, industry, and governing law. Then you get a clear recommendation on whether to accept or push back.
You don’t have to hunt for answers or guess the right approach anymore. Your past becomes your strength.
Point Ivo at your contracts, and Benchmarks begins its work.
Ivo evaluates each clause in the contracts you’re reviewing and compares them against your previously executed agreements. You can see how often your team has agreed to that exact provision before and what Ivo recommends based on that history.
When you want to understand why Ivo made its recommendations, you can see the exact language from your historical agreements. Then, you can pull relevant clauses from your contract library, compare and contrast them, and see the reasoning in seconds. The logic is always visible and traceable.
While Benchmarks works, a multi-step process is occurring to both retrieve the relevant documents your new contracts are being compared to and scored against. Here’s what’s happening under the hood:
Only facts relevant to this specific contract type are surfaced. Ivo uses LLM-driven relevance filtering to skip topics that don't apply, so you're never shown a benchmark for a provision that doesn't exist in the agreement you're reviewing.
This is what Benchmarks produces when assessing annual liability caps in a SaaS agreement review.
When a provision falls below your median (for example, a counterparty is proposing uncapped liability), Benchmarks will flag it, and Ivo's review agents will draft a redline toward your 50th-percentile position, using language drawn directly from your own past agreements.
Benchmarks is most valuable when you’re reviewing high-volume agreement types where your team has built up a considerable negotiating history. Here are the patterns we see most often:
1. Vendor and SaaS MSA review
Third-party paper · Typical library: 50–300 executed agreements
Benchmarks can measure liability caps, IP ownership, data processing terms, SLA minimums, and auto-renewal windows against your history with your vendors. When a vendor proposes a mutual indemnification clause you've never accepted, Ivo will flag it with a finding like “accepted 0 of 67 times.” It will then suggest language from the agreements where you held the line.
2. Customer contract negotiation
Own paper · Typical library: 100–500 executed agreements
Benchmarks tells you how many concessions you’ve made in the past on your own paper. If a customer is pushing for a shorter term than you typically accept—say, 12 months vs your standard 24—the feature will surface a pattern like 82% of comparable deals closed at 24+ months, giving your team a data-backed position to help you respond.
3. NDA and confidentiality review
Both paper types · High volume, lower stakes per agreement
For high-volume, lower-stakes agreements like NDAs, Benchmarks is useful. Your team has signed hundreds of these; Ivo can tell you whether a one-way NDA (instead of mutual) is something you've consistently pushed back on (accepted mutual structure 91% of the time), or whether it's worth the round trip.
Benchmarks adds to your existing playbook positions; it doesn’t replace them. When a benchmark overlaps with a playbook item, the playbook position always takes precedence. Where you have playbook coverage, benchmarks add historical context, and where you don't have playbook coverage, benchmarks can fill the gap automatically, surfacing facts your team has taken positions on through hundreds of past deals.
Every benchmark recommendation shows its sources, which are the verbatim clauses from your historical agreements that define the distribution of the legal positions.
Benchmarks activates when you connect a repository of your executed agreements to Ivo. The minimum threshold is 10 comparable contracts in a given category, although most teams find meaningful benchmarks emerging around 25–50 agreements and richer distributions forming at 100+.
Once your repository is indexed, Benchmarks runs automatically on every new review. There's nothing to configure: Ivo extracts the market parameters from any agreement you review and pulls the right historical comparisons.
Benchmarks is now generally available (GA). See it in action.
Playbooks are how you tell Ivo Review your standards (e.g., the positions you take, the language you prefer, the lines you won't cross) so its redlines track to how your team actually works.
With Playbook Builder, you start from the contracts you already have. Point Ivo at the agreements in your repository, or upload from your local folders, and it will direct a few questions to you about which agreements to learn from and what to focus on. It then begins to draft the playbook from your own contracts, templates and guidance documents: standard positions, fallback language, all learned from your own precedents. You review every position in the output, choose whether it stays personal or goes to your whole organization, and save it as a playbook in a single step.
Most teams carry a long list of agreement types they've never found the time to build a playbook for at all. Now you can build those yourself, in minutes.
Every position Playbook Builder drafts comes from your own agreements, with a citation back to the contract it came from. You're never taking the output on faith as you can trace each position to the source and confirm it reflects how your team actually contracts.
Because you build it yourself in minutes, you can finally cover the agreement types your team has never gotten around to, the ones that have sat on the someday list while higher-priority work came first. More of your review runs against a real playbook instead of none.
You decide which contracts Ivo learns from and review every position before it's saved. And because creating playbooks is governed by role, administrators control who can author them and whether a playbook stays personal or becomes a company standard, so self-serve speed never costs you a single source of truth.
Playbook Builder gives your team a faster way to turn its own contracts into working playbooks, with the guardrails to keep your standards consistent. If you need any additional support building playbooks, our solutions attorneys are always here to help.
Connect with us now to learn how we can streamline your contract review process
